Education-to-Work Transitions: Entry-Level Pathways Eroded by AI?

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Introduction

As artificial intelligence (AI) tools have rapidly entered the workplace, many worry that entry-level jobs and internships – the “stepping stones” from school to career – are disappearing. These roles have traditionally given new graduates hands-on training and a pathway into good careers. The question today is whether generative AI (like ChatGPT, released in late 2022) and related automation have actually reduced entry-level hiring. To answer, we look at data on internship and junior role postings, campus recruiting surveys, and early-employment outcomes. We then consider the effects on recent graduates (especially those in fields most exposed to AI, like computer science or routine business roles) and discuss how policy or employers might preserve these on-ramps.

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Introduction As artificial intelligence AI tools have rapidly entered the workplace, many worry that entry-level jobs and internships, the stepping stones from school to career, are disappearing. These roles have traditionally given new graduates hands-on training and a pathway into good careers. The question today is whether generative AI, like ChatGPT, released in late 2022, and related automation have actually reduced entry-level hiring. To answer, we look at data on internship and junior role postings, campus recruiting surveys, and early employment outcomes. We then consider the effects on recent graduates, especially those in fields most exposed to AI, like computer science or routine business roles, and discuss how policy or employers might preserve these on-ramps. Trends in entry-level postings and internships. Multiple data sources suggest a pullback in the pipeline that once funneled students into careers. For example, a technology news review found that tech internship postings fell by about 30% between 2023 and 2025. The same report noted that major tech companies are hiring fewer recent graduates, only about 7% of new hires, versus 9.3% a year earlier. A Fortune magazine analysis similarly found that entry-level job postings fell roughly 15% in 2024 for typical corporate roles. It also reported that the percentage of interns who received full-time offers dropped to 51%, the lowest rate in over five years. These declines match other observations. One analyst noted 13% fewer entry-level positions in coding, accounting, and admin over 2020 to 2023 in AI vulnerable fields. And the Stanford Digital Economy Lab reported a 16% drop in employment for 22 to 25-year-olds in AI-exposed occupations since late 2022. In short, postings for traditional junior roles, coding, data entry, customer support, and the like are down sharply while demand is growing for AI and data analysis skills. That said, the picture is complex. Surveys of employers show some stability in hiring plans overall. For instance, the National Association of Colleges and Employers found that about 60% of companies plan to hire the same number of new graduates in 2025 to 2026 as they did in 2024. In a survey of the class of 2026, about 44% of graduates already had an offer by graduation, similar to the class of 2025. So far, many firms say they are maintaining or even slightly increasing their entry-level hiring, driven by long-term pipeline planning, rather than cutting it drastically. On balance, however, dozens of reports in tech media, labor data, and academic studies point to a weakening entry-level market. The decline is most visible in sectors where AI can handle repetitive tasks. Tech internships and junior developer roles are dramatically down, and surveys indicate that companies are awarding fewer offers to their interns. In parts of the UK tech industry, for example, graduate job openings dropped by about 46% from 2024 to 2025. In summary, the pipeline is drying up. Fewer internship and junior positions are advertised, especially in tech-driven industries, even as demand for AI specialized roles grows. Campus recruiting and graduate surveys. What do campus recruiting statistics and student surveys say? In the U.S., college career surveys show a cautious market. NASA's fall 2025 recruiting survey projected only a 1.6% increase in hiring of new grads for 2026 over 2025. Essentially flat. While a strong post-pandemic rebound in 2021 to 2023 boosted offers, more recent classes are seeing a return to pre-COVID levels. For example, the class of 2026 averaged about 0.8 job offers per graduate before graduation. Roughly the same as the class of 2025. These figures suggest the early 2020s' boom in graduate hiring has eased. More detailed NACE data indicate that many employers plan to maintain hiring rates, focusing on succession planning for talent pipelines. At the same time, surveys show student concerns and expectations shifting. A large student survey reports that almost all students, 95%, said real paid work experience with an organization, i.e. internships, was their preferred way to engage employers. In other words, students want internships and early work experiences. A recent NACE report echoes this. The ability to complete an internship in a student's field was the most influential factor when choosing between equally qualified candidates. Yet with companies offering fewer internships, as noted above, students may find fewer opportunities to build those experiences. In short, campus recruiting data show that hiring of new grads is not brooming, but not wholesale collapsing either. Nearly half of 2026 graduates still received offers, and most employers aren't slashing entry-level programs. But students report struggling more than these broad numbers suggest, facing increased competition for fewer internship and junior roles. Research on early career employment, academic studies offer further insight. A Stanford University analysis using payroll data from ADP compared AI-exposed occupations like software development and customer support to others. It found that, since generative AI tools became widespread, employment for 22 to 25 year olds in AI-exposed jobs fell by 16% relative to their elders and to less exposed fields. Workers in fields unlikely to be automated, for example, some healthcare roles, saw stable or rising employment. Another working paper study by the U.S. Census confirmed a similar pattern. In the industries most exposed to AI, entry-level hires ages 22 to 24 dropped by about 12% in the 10 quarters after ChatGPT's release, 2023, compared to stable hiring in less exposed industries. These studies suggest that the decline is not due to a broad recession effect, but is concentrated precisely where AI can do routine tasks. Industry and news reports align with this view. For example, Tom's Hardware and Axios reported on a Stanford study showing 13-16% fewer entry-level jobs over recent years in fields that AI can largely automate, coding, routine data work, etc. These findings paint a clear picture. AI is acting like a canary in the coal mine for early careers. Entry-level and junior positions in tech and similar sectors are indeed shrinking faster than the economy as a whole. Importantly, these shifts have mainly happened through reduced hiring of newcomers rather than wage cuts. The studies note that salaries for remaining workers held steady even as headcounts fell. Not everyone agrees on the cause. Some analysts, like those at LinkedIn's economic graph and Handshake, emphasize that overall hiring has been weak because of higher interest rates and low worker turnover, not just AI. For instance, Handshake's research director notes that the drop in entry-level hiring began in early 2022, as the Federal Reserve started raising rates, and that older workers staying put is making fewer positions available for newcomers. LinkedIn likewise cautions sluggish hiring is not AI's fault, pointing to economic uncertainty as the bigger factor. In reality, both effects are likely at work. A tight labor market certainly compounded the problem, but AI-capable automation appears to have accelerated it in certain fields. Implications for graduates, scarring effects. When new graduates can't find entry-level jobs, it can leave a lasting scar, a weaker career trajectory just when it should be taking off. Research on past downturns and technology shocks offers guidance. Studies of cohorts who graduated during recessions or industry disruptions show they often suffer lower earnings and employment rates for years after. For example, economists found that college graduates who entered the job market around the Great Recession earned significantly less and took longer to find work than those from stronger year cohorts. Similarly, a recent analysis by Goldman Sachs looked at 40 years of data on workers displaced by technology. It found that over a 10-year span, those workers earned on average about 10% points less in real wage growth than comparable workers not displaced by tech. Workers in the hardest hit age range of 25 to 35 years old also accumulated less wealth and delayed home ownership. What does this mean for 2024 to 2026 graduates? If AI-driven automation reports translate into 10 to 15% fewer on-ramp jobs in some fields, these cohorts could face tangible setbacks. They may start careers later or in lower paying positions than they otherwise would have. Conversely, Goldman's research also showed a silver lining. Younger college-educated workers actually recovered more of their losses by switching careers or using new skills than older displaced workers did. In other words, Gen Z can be adaptable, but only if they get a chance. Each reduced entry-level position means one less chance for a graduate to gain experience. Over time, such gaps can erode skills and earnings. To sum up, substantial evidence suggests that if AI adoption continues to squeeze junior roles, there could be a generation-level impact. Fields most exposed, software, data, routine business operations, etc., will see their new professionals start on a tougher path. This scarring may last several years as economists expect early disadvantages to fade only slowly. Preserving entry-level opportunities is therefore crucial, not just for immediate jobs, but for the long-term health of the workforce. Preserving early career pipelines, strategies, and interventions. The good news is that steps can be taken by educators, employers, and governments to keep these career on-ramps open, even as AI transforms work. Education and skills training. Colleges and universities should integrate AI into their curricula for all students, not just tech majors. This doesn't mean every student must become a programmer, but they should learn to use an AI tools relevant to their field. Career services can also coach students on demonstrating AI-related skills on resumes and in interviews. For example, one NACE report notes that 95% of students value real paid work experience, so schools and advisors should help students secure internships and projects where they use AI to solve real problems. In short, education should pivot to produce AI literate graduates ready to add value beyond routine tasks. Employer apprenticeship and hiring practices. Many companies are finding creative ways to retain a robust entry-level pipeline. Some large employers are shifting from short summer internships to longer apprenticeship programs that combine training with work. For example, Accenture now fills about 20% of its entry-level positions through apprenticeships, and IBM and Microsoft have expanded similar programs focused on skills rather than degrees. When junior tasks are automated, internships should be redesigned to teach higher-level skills like critical thinking, interpersonal communication, and domain expertise that AI cannot provide. Crucially, top executives emphasize that budding employees often excel with AI. As Amazon's AWS CEO put it, replacing junior staff with AI is one of the dumbest ideas because young workers tend to be the most proficient AI users over time. Research backs that up. Trials show that less experienced workers gain more from AI tools than senior peers do. In other words, hiring juniors with AI training can actually boost productivity. Employers should therefore budget to train entry-level hires on AI tools rather than eliminating them and recognize that investing in new talent is still essential for future leadership. Public policy and partnerships, governments and industry groups can help by subsidizing training, organizing coalitions, and incentivizing youth hiring in AI sectors. For instance, the UK government recently launched an early careers jobs alliance with businesses and unions to study how AI is changing entry-level work. With £20 million backing, it will map those changes and share best practices for designing on-ramps. The plan includes funding an AI skills program for 400,000 disadvantaged students and rolling out free AI boot camps that guarantee internships or apprenticeships to participants. Similarly, Taiwan's government created an AI training program for new graduates that provides a fully funded year of hands-on AI education in partnership with universities, plus guaranteed industry internships and job placements. These are examples of proactive policies that build a bridge from education to work in the AI era. Other useful policy ideas could include tax credits or subsidies for companies that maintain robust internship apprenticeship programs, funding for community college and training programs in AI and data skills, and continued investment in career counseling that helps students align their interests with evolving job markets. On the education side, accreditation agencies might encourage or require demonstration that students have baseline digital and AI fluency upon graduation. Actionable advice for stakeholders. To be concrete, here are some steps each group can take now. Students and graduates proactively learn AI tools relevant to your field. Even basic prompt skills can help. Build portfolios of class projects or personal projects that use AI. Seek internships even in non-tech firms where AI skills are in demand. Highlight any AI-enabled achievements and applications since employers increasingly expect it. Colleges and career services partner with industry to understand which skills are needed. Offer workshops on AI and career skills and update resume guides to include a section for AI tools proficiency. Emphasize well-rounded skills, teamwork, problem solving, communication that AI cannot replicate. Employers, audit your roles to see which entry-level tasks can be augmented by AI, and redesign jobs so that human trainees learn the skills that AI can't handle. For instance, client communication or complex problem solving. Continue running internship apprenticeship programs instead of cutting them. It will pay off by creating trained talent. When hiring, test for problem solving and AI tool use rather than just credentials. Policymakers, support or expand youth training grants, apprenticeship schemes, and STEM AI education programs, particularly for underrepresented communities. Coordinate with workforce boards to monitor early career placements by sector and intervene if pipelines vanish. By combining these approaches, the shift toward AI can become a chance to upgrade the entry-level experience, not eliminate it. AI tools can handle rote tasks, freeing young employees to focus on learning strategic and creative skills. As one analysis concludes, AI is reshaping entry-level work more than outright eliminating it. With the right response, education to work pathways can be preserved and even strengthened for the class of 2024 to 2026. Conclusion. In summary, the avalanche of AI has indeed squeezed some traditional entry-level jobs, especially in tech and office administration fields. Job postings and surveys show notable declines in internships and junior roles in those sectors. Early career employment research confirms that young workers in AI-exposed fields have faced double-digit percentage drops in hiring. However, the evidence also suggests broader economic forces at work, and that not all entry-level opportunities are gone. Vigilance and action are needed to avoid a long-term talent gap. Maintaining strong on-ramps from education to employment will require concerted effort. Companies should not simply swap junior staff for AI. Instead, they should use AI to empower new hires and expand their learning experiences. Educators and career centers must integrate AI literacy and focus on the uniquely human skills interns can develop. Governments can incentivize training programs and apprenticeships that connect students to work. By doing so, we can ensure that the next generation finds a pathway up the career ladder, even in an AI-driven economy. Tags, AI impact, entry-level hiring, internships, early career, labor market workforce development, apprenticeships, skills training, college to career, education to work transitions. All links to sources are available in the text version of this article. You can find the full article at can't findjob.com slash blog. Thanks for listening. If today's episode hit close to home, stop scrolling job boards that were built for this new reality. Check out Claw Earn on AIAagentStore.ai, the first jobs marketplace designed for both humans and AI agents. So you can start earning no matter which side of the AI revolution you're on.